Only models that have defined provider are present in a drop-down #259
Conversation
fix: ensure PKCE works for MCP Server auth (cgoinglove#256)
|
@nikolamilosevic86 is attempting to deploy a commit to the cgoinglove's projects Team on Vercel. A member of the Team first needs to authorize it. |
There was a problem hiding this comment.
Summary of Changes
Hello @nikolamilosevic86, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request refactors the AI model loading mechanism to dynamically include models in the application's dropdown only if their corresponding API provider keys are configured in the environment. This ensures that users only see and can select models for which they have valid access, improving usability and preventing errors.
Highlights
- Conditional Model Loading: Models from various AI providers (OpenAI, Google, Anthropic, xAI, Ollama, OpenRouter) are now loaded dynamically based on the presence of their respective API keys in environment variables.
- Dynamic Fallback Model Selection: The application's fallback model is now determined programmatically, prioritizing user-defined defaults, then OpenAI, then the first available model from any configured provider, or a local Ollama model.
- Refactored Model Definitions: The static model definitions have been restructured to
conditionalStaticModels, allowing for cleaner, conditional inclusion of models.
Using Gemini Code Assist
The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.
Invoking Gemini
You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands.
| Feature | Command | Description |
|---|---|---|
| Code Review | /gemini review |
Performs a code review for the current pull request in its current state. |
| Pull Request Summary | /gemini summary |
Provides a summary of the current pull request in its current state. |
| Comment | @gemini-code-assist | Responds in comments when explicitly tagged, both in issue comments and review comments. |
| Help | /gemini help |
Displays a list of available commands. |
Customization
To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.
Limitations & Feedback
Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.
You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.
Footnotes
-
Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩
There was a problem hiding this comment.
Code Review
This pull request refactors the AI model loading logic to be conditional based on whether a provider's credentials are present in the environment. This is a great improvement for robustness, as it ensures only available models are listed and used. The logic for selecting a fallback model is also made much more resilient. My review includes a couple of suggestions to further improve the code's clarity and remove a small piece of redundant logic.
Fixes #247